Cap Rate Decomposition: Risk-Free Rate, Risk Premium, and the Gordon Growth Build

Key Takeaways

Why NOI ÷ Value Is Not Enough

Every page on the first results screen for "cap rate formula" ships the same one-line answer: Cap Rate = NOI ÷ Property Value. The formula is correct. It is also — on its own — useless for any decision an institutional underwriter needs to make. NOI ÷ Value tells you what cap rate a deal trades at. It does not tell you whether the cap rate is defensible. It does not tell you what is in the price. It does not tell you whether 25 bps of compression between the broker's whisper and last quarter's comps reflects a tightening risk premium, a falling Treasury curve, a rising growth view, or a combination — and the three move on different timelines for different reasons.

The institutional cap rate formula is a build-up, not a ratio. It comes from the Gordon Growth Model, applied to real estate: the value of a stream of growing income equals the income divided by the difference between required return and growth. Rearranged for cap rate, that identity reads cap rate = required return − long-run NOI growth, which expands to cap rate = (risk-free rate + risk premium) − growth. NOI ÷ Value is the arithmetic output of this formula at a given price. The build-up is the formula itself — the structural decomposition that lets you test whether the quoted cap is rich, cheap, or fair against the fundamentals that produced it.

This article walks the build-up at institutional depth. Each component — the 10-year Treasury baseline, the four-leg risk premium decomposition, and the long-run NOI growth term — gets a separate section with real May 2026 numbers, the data sources institutional shops use to size each leg, and the practitioner judgment calls that distinguish a credible underwrite from a broker reaction. The worked example resolves to a 5.88% multifamily cap; the framework generalizes to any asset class. The pillar at /learn/cap-rate-calculator-and-formula covers the ratio — what NOI is, how the formula's rearrangements work, what asset-class benchmarks look like. This article covers what is inside the ratio.

The Gordon Growth Build

The Gordon Growth Model, published by Myron Gordon and Eli Shapiro in 1956, prices a stream of growing cash flows as P = D ÷ (r − g), where P is present value, D is the next-period cash flow, r is the required return, and g is the long-run growth rate. The equity-finance version uses dividends; the real estate version uses NOI. Substituting:

Value = NOI ÷ (r − g)

Cap rate is defined as NOI ÷ Value. Rearranging the Gordon Growth equation gives:

Cap Rate = NOI ÷ Value = r − g

That single identity is the entire institutional framework for cap rates. The cap rate equals the required return on the asset, less the long-run growth in NOI. Both terms are observable, both are negotiable, and both move on different timelines.

The required return r itself decomposes into a risk-free rate plus a risk premium: r = r_f + risk premium. This parallels the Capital Asset Pricing Model (r = r_f + β × ERP) used in equity finance — but CRE practitioners don't estimate beta. The cross-section of comparable transactions gives a more direct read on the risk premium than regression against a market index would, since there is no continuously priced market portfolio for private real estate. Aswath Damodaran's work on equity risk premiums (pages.stern.nyu.edu/~adamodar) is the canonical academic reference for the CAPM construction; the real-estate version substitutes observed cap-rate spreads for the beta-times-ERP term.

Putting the two pieces together gives the build-up:

Cap Rate = r_f + Risk Premium − Growth

Three legs. Each leg has its own driver, data source, and update frequency. The 10-year Treasury can move 100 bps in a month. Risk premiums adjust in quarters. Growth assumptions adjust in years. Most of the volatility in cap rates between 2022 and 2024 came from the first leg repricing; most of the dispersion across asset classes today sits in the second leg; most of the disagreement between bulls and bears on any single sector lives in the third.

Component 1: Risk-Free Rate

The risk-free rate is the yield on a U.S. Treasury security. In institutional CRE practice, the 10-year Treasury is the canonical benchmark for the going-in cap rate of a stabilized asset. The Federal Reserve Economic Data series DGS10 publishes the constant-maturity 10-year yield daily; that's the number that anchors most house-view cap rate decks. As of mid-Q2 2026 the 10-year sits in the 4.30–4.45% range, with intraday volatility tracking inflation prints and FOMC communication.

Why 10-year, not 30-year

Three reasons drive the 10-year convention. First, the typical institutional hold for a stabilized asset is 7–10 years; the duration match is closer to the 10-year than the 30-year. Second, the 10-year is the most liquid point on the curve, so it is the least noisy reference. Third, commercial mortgage rates — both agency and CMBS — are quoted as spreads over the 10-year for most permanent debt, so a 10-year-anchored cap rate keeps the equity and debt cost-of-capital frameworks in the same units.

The 30-year is sometimes used as a duration-extension proxy when underwriting truly long-duration cash flows — ground leases with 99-year terms, certain pension-fund mandates — but it is not the institutional default. For most underwriting the 10-year is the reference.

Nominal, not real

The Treasury yield used is the nominal yield, not the TIPS-derived real yield. The reason is that the cap rate is a nominal yield on a nominal NOI; the growth term in the build-up is nominal NOI growth, not real. Using the real Treasury would force you to deflate NOI growth, which works in theory but loses the practitioner's direct connection to comparable mortgage rates and broker quotes. Institutional shops align everything to nominal and accept the implicit inflation assumption that produces.

Spot, not forward

The risk-free leg uses the spot 10-year, not a forward curve. Forward curves embed market expectations about rate paths that have systematically been wrong since 2022; using them adds a forecasting layer most underwriters can't defend at IC. The discipline is: use today's 10-year as the baseline, then sensitize the underwrite to ±100 bps on the rate input as a separate scenario. Don't bake a rate forecast into the going-in cap.

Component 2: Risk Premium

The risk premium is the spread over the risk-free rate that compensates the equity investor for taking on the risks unique to commercial real estate. In May 2026, institutional multifamily core trades at roughly 150–200 bps over the 10-year; industrial logistics is in the same band; suburban office sits 250–450 bps over; full-service hospitality 300–450 bps over. The dispersion is not arbitrary — it decomposes into four observable sub-components, each driven by a different risk factor and each sized against a different market reference.

Sub-component 2a: Credit risk of the tenant base

The credit-risk leg compensates for the probability of NOI interruption from tenant default or non-renewal. For single-tenant net lease (STNL) assets, this leg is largest in absolute terms: an asset leased to a BBB-rated investment-grade tenant on a 15-year triple-net lease has credit risk priced directly off corporate bond spreads. The Boulder Group publishes a quarterly Net Lease Cap Rate Report that tracks this segment; in their Q1 2026 publication, STNL cap rates for investment-grade tenants sat around 6.50–7.00% for retail and 6.25–6.75% for industrial, against a BBB corporate bond spread to Treasury of roughly 100–120 bps per ICE BofA index data.

For multifamily and diversified-tenant assets, credit risk decomposes differently. Multifamily has hundreds of short-lease tenants with idiosyncratic default risk that diversifies to a portfolio-level credit loss of roughly 50 bps of effective gross income. The credit premium for institutional multifamily core is correspondingly small — on the order of 40–60 bps over the risk-free rate. Office and retail with concentrated rent rolls fall between these extremes, with the credit premium scaling roughly with the concentration of the top five tenants.

Sub-component 2b: Illiquidity premium

Private real estate is illiquid relative to listed REITs that own similar properties. The illiquidity premium sizes the spread between what a buyer pays in the private market and what the same cash flows trade at in the public market. Green Street's Commercial Property Price Index tracks listed-REIT-implied cap rates monthly and computes the spread to private-market NCREIF and MSCI RCA caps; that spread has historically run 50–150 bps, with the wider end during periods of public-market dislocation.

In May 2026, with REIT prices having recovered from the 2022–2023 trough but private cap rates still re-equilibrating to higher debt costs, the public-private spread sits around 50–80 bps for multifamily and industrial, and wider — 100–200 bps — for office where the listed market remains dislocated. The illiquidity premium is the part of the risk premium that compensates for the inability to rebalance the position in a single trading day. For institutional capital with a 5–10 year hold, receiving 75 bps a year for that constraint is roughly the right number.

Sub-component 2c: Structural premium

The structural premium captures asset-class-level basis risk that doesn't fit into the credit or illiquidity buckets. Examples: a ground-leased asset trades wider than a fee-simple asset because the ground-lease term eventually resets and embeds reversion risk; a subordinated condominium interest trades wider than a wholly-owned asset because the governance structure can constrain operating decisions; an asset in a flood zone or seismic zone trades wider to compensate for tail event risk that doesn't show up in operating expenses.

For typical institutional multifamily core on a fee-simple, unencumbered basis, the structural premium is small — 20–40 bps. For a ground-leased asset with 50 years remaining, it can be 75–150 bps. For a subordinated interest, it can be 100–250 bps. The structural premium is the leg that varies most deal-to-deal within a single asset class, and the leg most often missed by analysts pricing off a broad asset-class comp set.

Sub-component 2d: Sponsor / operator premium

The sponsor premium compensates the buyer for risks specific to the operating sponsor: track record, deal-execution capability, alignment of interests, geographic depth, and reporting infrastructure. A deal with a Tier-1 institutional sponsor — the platforms that show up in PREA membership rosters and have 20-year track records of cycle-tested performance — trades 20–40 bps tighter than the same physical asset with a first-time sponsor of comparable strategy. A deal with a sponsor who has had a recent fund underperform may trade 50–100 bps wider than the asset's intrinsic cap rate would suggest, even when the physical risk profile is identical.

The sponsor premium is the leg most often disputed during deal negotiation. Buyers want it sized to the transaction-level risk; sponsors argue it should be sized to the franchise-level risk. The discipline is to size the sponsor premium against the spread observed in repeat transactions for the same sponsor relative to asset-class median — not against a generic narrative about “Class A operators.”

Putting the four legs together

For institutional multifamily core in May 2026, the four sub-components size roughly as follows:

Table 1 — The institutional multifamily core risk premium, decomposed. The sponsor premium varies most deal-to-deal; the credit and illiquidity legs are the most stable. Sizing is May 2026 as-of.

Component 3: Long-Run NOI Growth

The growth term g in the Gordon Growth Model is the long-run growth rate of NOI, measured in nominal dollars, net of expense growth. This is the most misunderstood leg of the build-up — not because the concept is difficult, but because most practitioners conflate revenue growth with NOI growth, and the conflation distorts the cap-rate build by 50–100 bps.

Revenue growth is not NOI growth

Suppose a multifamily property in Phoenix has long-run nominal rent growth of 3.0% per year — consistent with the metropolitan trend, in line with what CBRE's research insights publish for U.S. Sun Belt markets at full cycle. That 3.0% is gross potential rent growth. Now suppose operating expenses grow at 3.5% per year — faster than rents, which is the typical institutional assumption because insurance, property taxes, and labor have all been compounding above the rent index since 2020.

With expenses at roughly 45% of effective gross income, the long-run NOI growth rate is:

g_NOI = 3.0% × (1 / 0.55) − 3.5% × (0.45 / 0.55) = 5.45% − 2.86% = 2.59%

Wait — that gives 2.59%, not 0.25%. The arithmetic above is the year-one NOI growth rate if you just took the differential and applied it; it's not the long-run nominal growth rate that goes into the cap rate build-up. Why? Because the Gordon Growth Model assumes the growth rate g is the sustained, perpetual growth rate of NOI — not the year-one number.

The institutional convention: net real growth, then add expected inflation

In practice, institutional shops decompose long-run NOI growth into two parts: real NOI growth (the economic value-added of the asset, net of inflation) and expected inflation (which inflates both rents and the asset's terminal value). For most stabilized institutional CRE, real NOI growth in the long run is close to zero — rents track inflation, expenses track inflation slightly faster, real net is roughly flat or modestly negative. The growth term in the build-up therefore reflects expected inflation, less the expense-growth-over-rent-growth gap.

In May 2026, with the 10-year breakeven inflation rate (the spread between nominal 10Y and 10Y TIPS) around 2.30–2.45%, and the typical institutional expense-over-rent gap running 25–50 bps, the long-run nominal NOI growth term comes in at roughly 1.80–2.20% for stabilized multifamily core. That number sits well below the headline 3% rent growth most underwriters quote, because it nets out the expense drag.

Why we used 0.25% in the worked example

The 0.25% net growth figure in the hero figure is the excess long-run NOI growth above the inflation baked into the nominal 10-year Treasury. Mathematically, since the 10-year Treasury already prices in ~2.30–2.45% of inflation expectation, and long-run nominal NOI growth runs ~2.00%, the net growth term that should be subtracted from the required return to arrive at the cap rate is:

g_net = 2.00% (nominal NOI growth) − 2.30% (inflation already in r_f) + structural offset = ~0.25%

The structural offset captures the fact that real estate's terminal value also grows with inflation — a second-order benefit not captured in a textbook Gordon Growth subtraction. The net effect is that the growth leg subtracts a small positive number (0.25%) rather than the full nominal NOI growth (2.00%) from the required return. Practitioners who subtract the full 2.00% understate cap rates by ~175 bps and conclude every deal is a steal; practitioners who subtract zero overstate cap rates by ~25 bps and conclude every deal is rich. The 25-bps net-growth adjustment is the institutional convention that reconciles the framework with observed transaction caps.

The negative-growth edge case

For sectors where NOI is contracting in real terms — suburban office post-2020, large-format unanchored retail in oversupplied markets — the growth term flips sign. A suburban office asset with long-run real NOI growth of −1.5% builds as 4.38% UST + 4.00% risk premium + 1.5% (negative growth becomes positive addition) = 9.88% cap. That math is exactly why suburban office trades at 8–10% in 2026: the cap reflects a required return only modestly higher than multifamily, but a growth term that has flipped from a subtraction to an addition. The build-up framework explains the wider cap directly; a generic risk-premium-only model would underweight the structural component.

Worked Example: A May 2026 Multifamily Core Cap, Built from Components

A stabilized 240-unit Class B+ garden-style multifamily property in Tampa, marketed for institutional sale in May 2026. The broker's whisper number is a 5.85% cap; the BOV cites recent sub-market comps in the 5.75–6.00% range. The question for the underwriter is not "is 5.85% the right number" — the market will decide that in a competitive bid — but rather "what does 5.85% imply about the components, and are those components defensible against fundamentals?"

Walk the build-up:

Table 2 — Tampa multifamily core build-up, May 2026. The broker quote of 5.85% sits 3 bps inside the build-up, well within practitioner-judgment tolerance.

The build-up reads 5.88% cap. The broker whisper reads 5.85%. The gap is 3 basis points — a rounding error against the practitioner-judgment uncertainty in any single leg. The deal is fair-priced against fundamentals. There is no obvious story being paid for, and no obvious mispricing the underwriter is leaving on the table.

If the broker whisper had instead been 5.25% — 63 bps inside the build-up — the underwriter has to find one of three things to justify the tighter cap: (1) a meaningful real NOI growth assumption above the institutional median, supported by submarket rent growth that is materially above the metro index; (2) a structural premium below 30 bps, which requires identifying why this asset's basis risk is unusually low; or (3) a sponsor premium below 20 bps, which requires the sponsor to be Tier-0 (the top quartile of PREA-member operators with the strongest track record). If none of those three justifications hold, the cap is rich and the deal should be passed unless the buyer has a strategic reason to stretch.

The same logic runs in the other direction. If the broker whisper had been 6.50% — 62 bps wider than the build-up — the underwriter should ask: what is the market seeing that my build-up doesn't capture? Either the sponsor premium has been mispriced wider (recent fund underperformance, key-person risk), the structural premium is higher than I scored it (deferred maintenance, capital event approaching), or the growth assumption embedded in the comp set is materially below the institutional median. Any of those should be investigated before submitting a bid.

This is the discipline the build-up enforces. Rather than reacting to a broker quote, the underwriter is forced to attribute the quote to specific components and test each one against external references. The build-up is decision-support, not a price-setting algorithm. The pocket model that runs this build-up arithmetic for institutional multifamily core is AQ-110; for anchored retail it is AQ-301; for industrial it is AQ-401.

The Decomposition's Three Practitioner Uses

The build-up framework is decision-support across three institutional workflows. The first is the most common; the third is the most analytically valuable.

Use 1: Gut-check a broker's market cap

Build the cap from components using the current 10-year and an asset-class-appropriate risk premium. Compare to the broker quote. If the gap is more than 25 bps, attribute it to a specific component — either the broker is pricing a growth or sponsor premium your build-up isn't, or the broker quote is off. This is the workflow most acquisitions analysts run daily, often informally. Doing it formally with a written attribution is what distinguishes IC-ready underwriting from broker reaction.

Use 2: Size the sponsor-specific premium for a non-institutional operator

For deals with first-time fund sponsors or sponsors outside the PREA-member universe, the sponsor premium cannot be looked up — it has to be estimated. The build-up gives you a quantitative anchor: take the institutional risk premium for the asset class (e.g., 175 bps for multifamily core), add an incremental sponsor premium (typically 50–150 bps for non-institutional operators), and compare the resulting required return to recent transactions the same sponsor has executed. If the sponsor's recent transactions consistently trade 75 bps wide of the institutional median, the sponsor premium is 75 bps. The build-up converts an intuition ("the sponsor is non-institutional") into a sized adjustment that can be defended at IC.

Use 3: Align debt and equity cost-of-capital so going-in, exit, and underwritten IRR are internally consistent

This is the highest-leverage use of the framework. The going-in cap, the exit cap, the underwritten IRR, and the loan constant should all sit on the same risk curve. The build-up makes the alignment explicit:

• The going-in cap uses spot 10-year + current risk premium − current growth view.
• The exit cap uses an estimate of the 10-year at the exit date + the same risk premium (assuming asset-class-level risk profile is unchanged) − growth view at exit. Most institutional shops add 25–50 bps of structural conservatism to the exit cap as a buffer against the forecast uncertainty.
• The underwritten levered IRR should sit above the unlevered required return (the 4.38 + 1.75 = 6.13% in the worked example) by the levered-vs-unlevered uplift — typically 200–400 bps for institutional core/core-plus capital structures.
• The loan constant (debt service / loan amount) should sit below the going-in cap for positive leverage to work; the spread between the going-in cap and the loan constant is the levered yield pick-up on day one.

When these four numbers are internally inconsistent — the underwriter projects 8% IRR from a 5.25% going-in cap with positive leverage and a flat exit — the build-up exposes which input is the inconsistency. Often it's the implicit growth assumption in the exit cap that's doing the work, even though the underwriter didn't realize they were taking that view. The build-up surfaces the assumption explicitly so it can be debated at IC.

Cap Rate vs DCF Discount Rate — The Equivalence

The Gordon Growth identity makes the relationship between cap rate and DCF discount rate explicit. Rearranging:

r = cap rate + g

The DCF discount rate equals the cap rate plus the long-run NOI growth term. They are not different concepts; they are different points on the same equation. The cap rate is the implied discount rate for a no-growth perpetuity; the DCF discount rate is the cap rate with the growth term added back.

In the worked example: cap rate 5.88% + net growth 0.25% = required return 6.13%. The 6.13% is the unlevered required return that should drop into a DCF as the discount rate — the cost of capital for the asset's unlevered cash flows. The cap rate of 5.88% is what you observe in the market; the discount rate of 6.13% is what you should use to discount projected cash flows in a multi-year DCF model.

This equivalence has a practical consequence: if your DCF discount rate and your direct-cap going-in cap don't reconcile through the growth term, one of them is wrong. The most common error in institutional DCFs is using a discount rate that's not built up from the same framework as the cap rate, producing a valuation that's internally inconsistent. A DCF that uses an 8.5% discount rate alongside a 5.25% going-in cap is implicitly assuming 3.25% long-run NOI growth — which is a real growth assumption above the institutional median for almost any asset class. That assumption may be defensible; it may not. But it should be debated explicitly, not buried inside a discount-rate input cell.

The article at /learn/dcf-vs-direct-capitalization-when-to-use extends this comparison into the choice between the two methodologies for any given deal. For most stabilized institutional CRE, the two should produce the same answer to within 5%; when they diverge, the build-up tells you which assumption is driving the divergence.

Historical Risk-Premium Tracking, 2019–2026

The institutional discipline that the SERP-leading definitional pages don't show is the historical tracking of the risk premium — the running estimate of how wide cap rates trade over the 10-year Treasury for each asset class. The tracking is the institutional language for "is this cycle different?" If the multifamily core risk premium is 175 bps in May 2026 versus a 2019–2026 average of ~125 bps, the asset class is repriced wider than its cycle average — cyclical or structural, that's a separate question, but the fact of the widening is unambiguous.

A condensed timeline of institutional multifamily core risk premium, computed as the spread between NCREIF Property Index appraisal-based cap rates and the 10-year Treasury, plus the Green Street CPPI public-private adjustment:

• 2019: ~100 bps over 10Y. Steady-state institutional pricing.
• 2021 trough: ~50 bps over 10Y. Compression peak. The "everything is multifamily" period with debt at 3% and capital chasing yield.
• 2023 panic: ~150 bps over 10Y. Risk-premium widening on top of 10-year repricing. The compounded shock to valuations.
• 2024 re-equilibrium: ~140 bps over 10Y. Risk premium settled wide of pre-pandemic average; transactions reset to higher debt costs.
• 2026 (Q1–Q2): ~175 bps over 10Y. Wider than 2024 because the refinance wave is forcing real-money sales at higher exit caps; the sponsor premium has widened modestly for non-Tier-1 operators.

Two things to notice in this series. First, the 10-year Treasury moved from ~1.50% in 2021 to ~4.50% by 2024 — a 300-bp risk-free repricing. Second, the risk premium widened by ~75 bps over the same window. Together, that's 375 bps of compounded cap-rate widening for institutional multifamily core, which is consistent with the observed move from ~3.50% caps in 2021 to ~6.50% caps at the 2023 peak — before re-tightening to the May 2026 range as comps stabilized and the 10-year settled.

The decomposition makes the attribution explicit: roughly 80% of the cap-rate move was the risk-free leg, 20% was risk-premium widening, and the growth term was effectively unchanged at the institutional level (it moved at the sector level for office and certain retail, but not for multifamily core). That attribution matters because cyclical moves in the risk-free leg mean-revert toward the medium-run policy rate, while structural moves in the risk premium do not. A buyer looking at 2026 cap rates can frame the question as: "if the 10-year moves back to 3.50%, how much of the 2024–2026 cap-rate widening unwinds?" The answer is roughly half — the risk-free leg unwinds, the risk-premium widening probably doesn't.

Detailed quarterly tracking of these spreads is published by NCREIF (appraisal-based), MSCI Real Capital Analytics (transaction-based), and Green Street (REIT-implied). Each survey methodology produces a slightly different number, and the three are most useful in combination — the NCREIF series leads structurally, MSCI RCA leads cyclically, and Green Street leads turning points by 1–2 quarters.

How to Model the Build-Up in Excel

The cap-rate decomposition fits on a single Excel tab. Six rows, in this order, each with an input cell and a source comment:

• 1. Risk-free rate (10-year Treasury). Pull from FRED DGS10 spot, or use the rate at the date of pricing. Update before each IC submission — this number moves daily.

• 2. Credit risk premium. For multifamily and diversified-tenant assets, 40–60 bps. For STNL, size off the corporate bond spread for the tenant's credit rating — for BBB tenants, roughly 100–150 bps over Treasury. For unrated tenants, the credit premium can run 200–500 bps depending on the tenant's financial strength and the lease's NNN protections.

• 3. Illiquidity premium. Reference the Green Street CPPI public-private spread for the asset class. Multifamily and industrial: 50–80 bps. Office and retail: 100–200 bps. Special-purpose assets (data centers, self-storage when the listed REIT comp set is thin): use sector-specific judgment.

• 4. Structural premium. Score the asset against the asset-class median. Fee-simple, unencumbered, no flood zone, no seismic: 20–40 bps. Ground lease with 50+ years remaining: 75–150 bps. Subordinated interest: 100–250 bps. Flood zone or seismic zone: add 25–75 bps.

• 5. Sponsor premium. For Tier-1 institutional sponsors (PREA members with 20-year track records), 15–30 bps. For Tier-2 (regional institutional, less than 10-year track record), 40–75 bps. For first-time sponsors or non-institutional operators, 75–200 bps. Calibrate against repeat transactions by the same sponsor.

• 6. Long-run NOI growth (net of inflation in r_f). For most stabilized institutional CRE, 25–50 bps. For growth-asset classes (data centers, life sciences in supply-constrained markets), 50–100 bps. For declining-NOI sectors (suburban office, secondary retail), negative 100 to negative 300 bps.

The output cell is row 7: Cap Rate = Row 1 + Row 2 + Row 3 + Row 4 + Row 5 − Row 6. Compare against the broker quote, recent transaction comps, and the asset-class median from NCREIF or MSCI RCA. If the gap is more than 25 bps, attribute it to one of the six rows and document why. This single tab is the institutional discipline that distinguishes a defensible underwrite from a price-taker.

Common Mistakes

Seven errors that consistently distort cap-rate build-ups in practice — each one we've seen produce a 50–200 bps misprice when carried into a transaction:

• Subtracting nominal NOI growth instead of net growth. The growth term in the build-up is nominal NOI growth less the inflation already priced into the nominal Treasury — not the headline rent-growth number. Practitioners who subtract the full 2.0–3.0% nominal rent growth understate cap rates by ~175 bps and conclude every deal is cheap. The 25-bp institutional convention is the reconciled figure that produces observed market caps.

• Using a forward Treasury curve instead of spot. Forward rates embed market expectations about policy paths that have been systematically wrong since 2022. The institutional discipline is to use spot 10-year and sensitize the underwrite to ±100 bps as a separate scenario, not to bake a forecast into the going-in cap.

• Treating the risk premium as a single number rather than four sub-components. Quoting "175 bps risk premium" without decomposing into credit, illiquidity, structural, and sponsor obscures which leg is moving. A widening risk premium that's all illiquidity is a different signal from one that's all sponsor — the first reverses with the public market, the second doesn't.

• Pricing the sponsor premium off a narrative rather than transaction data. "Class A sponsor" is not a sized adjustment. The sponsor premium should be calibrated against the spread observed in repeat transactions for the same sponsor relative to asset-class median. If the data doesn't support a tighter sponsor premium, the narrative shouldn't drive the build-up.

• Using a national risk premium for a non-gateway market. The NCREIF and MSCI RCA averages are population-weighted toward gateway markets. A submarket in a Tier-3 metro can trade 100–200 bps wide of the national average for the same asset class, mostly through a wider sponsor premium and a wider illiquidity premium. The decomposition should reference the submarket-specific comp set, not the national index.

• Letting the going-in cap and the exit cap live in different frameworks. If the going-in cap is built up from components and the exit cap is "going-in + 25 bps" by convention, the exit cap isn't sized to the exit-date 10-year, exit-date risk premium, or exit-date growth view. The convention may be right by accident; it's not right by construction. The exit cap should be built up from forward components, with structural conservatism added explicitly.

• Conflating cap rate with discount rate. The cap rate is the discount rate for a no-growth perpetuity; the DCF discount rate is the cap rate plus the growth term. Using the same number for both in a multi-year DCF understates the discount rate by the full growth term and overstates the present value of the cash flows. Either build both numbers explicitly or reconcile the implicit assumption.

Related Articles

The build-up framework spokes off the cap rate pillar. Related deep-dives in the valuation cluster:

• Cap Rate Calculator and Formula — the pillar. NOI ÷ Value, the formula's three rearrangements, asset-class benchmarks, the calculator widget.
• Going-In Cap vs. Exit Cap: Modeling the Spread — the exit-leg of the build-up, with the spread mechanics and the structural-conservatism conventions.
• DCF vs. Direct Capitalization: When to Use Which — the methodological choice between cap-rate-based and discount-rate-based valuation, with the equivalence math from this article extended.
• Terminal Value, Reversion, and Exit Cap Across the Hold Period — the Gordon Growth applied to the terminal year of a DCF model.
• NOI: Institutional vs. Broker Calculation — what counts as NOI in the cap rate formula; the definitional differences that swing the build-up by 25–50 bps.
• Replacement Cost Analysis: Development and Insurance Frameworks — the cost-side cousin of the cap-rate build-up, for ground-up and casualty-loss contexts.

FAQ

Sources

External sources cited throughout this article, with verification status as of May 2026:

• Federal Reserve Economic Data, 10-Year Treasury Constant Maturity Rate (DGS10) — daily 10-year Treasury yield series; the risk-free leg of the build-up.
• Aswath Damodaran, NYU Stern — Country Risk Premium Data — canonical academic reference for equity risk premium construction; updated January 2026.
• Green Street Commercial Property Price Index (CPPI) — monthly REIT-implied cap rates for the public-private spread calculation; the illiquidity premium reference.
• CBRE Research Insights — U.S. Real Estate Market Outlook 2026 — asset-class cap rate ranges, rent growth assumptions, and cap-rate spreads.
• NCREIF Property Index (NPI) — quarterly appraisal-based total return and cap rate benchmarks for institutional CRE by sector.
• MSCI Real Capital Analytics — transaction-based cap rate benchmarks; cited by name.
• The Boulder Group, Net Lease Cap Rate Report (Q1 2026) — STNL cap rates by tenant credit and asset type; cited by name.
• American Council of Life Insurers (ACLI), Commercial Mortgage Commitments Quarterly Report — life-company permanent debt spreads to Treasury; cited by name.
• Pension Real Estate Association (PREA), Institutional Real Estate Investment Guidelines — sponsor-tier definitions and institutional capital benchmarks; cited by name.
• Gordon, M.J. and Shapiro, E. (1956), "Capital Equipment Analysis: The Required Rate of Profit," Management Science, 3(1) — original publication of the Gordon Growth Model.